Up to now, Internet has been developed into a platform irreplaceable for people's work, life, social contact and operation. As an extension and evolution direction of conventional Internet, mobile Internet has been developed more rapidly in the past two years. Nowadays, more and more users are enabled to access the Internet for rich data services and Internet service contents through high-speed mobile networks and powerful intelligent terminals. Mobile Internet has become one of major manners for people throughout the world to access the Internet.
With arrival of the mobile Internet era, security problems of terminals and networks become more and more serious, users are frequently attacked by hackers, Trojans and malware, and loss or stealing of mobile phones, stealing of bank accounts, embezzlement of cash, illegal use of user Identities (IDs) and the like are common. Various potential network security hazards arouse worries of people about network security, and an ID authentication mode of “username+password” may not meet a network security requirement any longer. Biological features such as faces, voiceprints, fingerprints, irises and the like have the features of uniqueness, stability, unduplicatedness and the like, and these features may be utilized to implement secure and convenient ID recognition to overcome the shortcomings and defects of forgetting, stealing, leakage, cracking and the like of conventional authentication manners of signatures, passwords, magnetic cards, Integrated Circuit (IC) cards and the like. Along with continuous development and perfection, a biological feature recognition technology is widely applied to a network security system, draws attention of experts and the masses of users, and is preferred for terminal login, ID authentication and public security management.
Although a biological feature recognition technology is advanced and reliable, its security and reliability are based on security of biological feature data, and how to ensure reality and validity of biological feature data and avoid the biological feature data being stolen and leaked is a practical problem now. Leakage of biological feature data in a network transmission process may result in a catastrophic consequence. Cases of illegally acquiring and duplicating biological features of others and cheating a computer system for false authentication with the duplicated biological features also happen occasionally.
In order to ensure security of ID recognition with a biological feature, a voiceprint authentication system is proposed in a conventional art, and the authentication system mainly performs content analysis on a speech provided by a user, performs mode matching on an analyzed speech content and a password content, then performs speech validity detection on speech data provided by the user, and if the speech data is valid data naturally produced by the user, further analyzes speech features to judge whether the speech passes voiceprint authentication or not.
The abovementioned authentication manner improves security of ID recognition with a biological feature to a certain extent although, the authentication manner is undiversified, and a voiceprint is easily faked or counterfeited to cause false authentication, which greatly reduces security authentication effectiveness.
For the problem of undiversified biological feature recognition and authentication manner in a related technology, there is yet no effective solution.